scholarly journals Measuring Health Vulnerability: An Interdisciplinary Indicator Applied to Mainland Portugal

2019 ◽  
Vol 16 (21) ◽  
pp. 4121 ◽  
Author(s):  
Oliveira ◽  
Vidal ◽  
Ferraz ◽  
Cabeda ◽  
Pontes ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Progress Monitoring ◽  
Statistical Tests ◽  
Composite Index ◽  
Reference Method ◽  
Vulnerability Index ◽  
Health Determinants ◽  
Life Conditions ◽  
Mainland Portugal ◽  
Health Vulnerability

Health promotion and inequality reduction are specific goals of the United Nations 2030 Agenda, which are interconnected with several dimensions of life. This work proposes a composite index SEHVI—socioeconomic health vulnerability index—to address Portuguese population socioeconomic determinants that affect health outcomes. Variables composing SEHVI are aligned with the sustainable development goals considering data and times series availability to enable progress monitoring, and variables adequacy to translate populations’ life conditions affecting health outcomes. Data for 35 variables and three periods were collected from official national databases. All variables are part of one of the groups: Health determinants (social, economic, cultural, and environmental factors) and health outcomes (mortality indicators). Variables were standardized and normalized by “Distance to a reference” method and then aggregated into the SEHVI formula. Several statistical procedures for validation of SEHVI revealed the internal consistency of the index. For all municipalities, SEHVI was calculated and cartographically represented. Results were analyzed by statistical tests and compared for three years and territory typologies. SEHVI differences were found as a function of population density, suggesting inequalities of communities’ life conditions and in vulnerability to health.

scholarly journals Efficiency of the primary health care policy in Brazilian municipalities: an application of the Pearl’s Structural Causal Model

2021 ◽  
Author(s):  
Darlan Christiano Kroth ◽  
Raquel Rangel de Meirelles Guimarães
Keyword(s):  
Health Policy ◽  
Health Outcomes ◽  
Health Care Policy ◽  
Causal Model ◽  
Causal Effect ◽  
Vulnerability Index ◽  
Future Research ◽  
Policy Performance ◽  
Unified Health System ◽  
Health Vulnerability

ABSTRACT Background In recent years, public health policies and their effects on improving health outcomes have been gaining prominence in the economic literature and on the agenda of international organizations. Objective This study aims to evaluate the causal effect of the “Pacto pela Saúde” (Pact for Health) program on health policy performance in terms of a Health Vulnerability Index (HVI) of Brazilian municipalities from 2006 to 2013. The “Pacto pela Saúde” program is the current operational standard of the Brazilian Unified Health System (SUS). One of the main guidelines of this program was to improve health policy governance. Method The effect resulting from efficiency gains of the participation of municipalities in the health policy on the HVI was estimated by the Pearl’s Structural Causal Model. Results The results indicate a positive and significant impact of efficiency management on the reduction of health vulnerability in the municipalities. The Pearl’s Causal Model and the back-door criterion of causal identification were employed to calculate the effects of the “Pacto pela Saúde” program on the HVI. Conclusion The use of Pearl’s method in this study contributed to a more comprehensive analysis of the effects of the “Pacto pela Saúde” program on health outcomes and, therefore, its use in future research on the analysis of public policies is recommended.

scholarly journals Analyzing Spatial Patterns of Health Vulnerability to Drought in the Brazilian Semiarid Region

2021 ◽  
Vol 18 (12) ◽  
pp. 6262
Author(s):  
Júlia Alves Menezes ◽  
Ana Paula Madureira ◽  
Rhavena Barbosa dos Santos ◽  
Isabela de Brito Duval ◽  
Pedro Regoto ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Social Determinants ◽  
Vulnerability Index ◽  
Health Determinants ◽  
Semiarid Region ◽  
Human Welfare ◽  
Promotion Policies ◽  
Brazilian Semiarid ◽  
Health Vulnerability

Health determinants might play an important role in shaping the impacts related to long-term disasters such as droughts. Understanding their distribution in populated dry regions may help to map vulnerabilities and set coping strategies for current and future threats to human health. The aim of the study was to identify the most vulnerable municipalities of the Brazilian semiarid region when it comes to the relationship between drought, health, and their determinants using a multidimensional index. From a place-based framework, epidemiological, socio-economic, rural, and health infrastructure data were obtained for 1135 municipalities in the Brazilian semiarid region. An exploratory factor analysis was used to reduce 32 variables to four independent factors and compute a Health Vulnerability Index. The health vulnerability was modulated by social determinants, rural characteristics, and access to water in this semiarid region. There was a clear distinction between municipalities with the highest human welfare and economic development and those municipalities with the worst living conditions and health status. Spatial patterns showed a cluster of the most vulnerable municipalities in the western, eastern, and northeastern portions of the semiarid region. The spatial visualization of the associated vulnerabilities supports decision making on health promotion policies that should focus on reducing social inequality. In addition, policymakers are presented with a simple tool to identify populations or areas with the worst socioeconomic and health conditions, which can facilitate the targeting of actions and resources on a more equitable basis. Further, the results contribute to the understanding of social determinants that may be related to medium- and long-term health outcomes in the region.

Measuring the Employment Vulnerability Among Female Workers in Uttar Pradesh

2021 ◽  
Vol 15 (2) ◽  
pp. 307-322
Author(s):  
Nomita P. Kumar ◽  
Achala Srivastava
Keyword(s):  
Women Workers ◽  
Composite Index ◽  
Uttar Pradesh ◽  
Principal Component ◽  
Vulnerability Index ◽  
Informal Workers ◽  
Garment Workers ◽  
Principal Component Loading ◽  
And Gender ◽  
Component Loading

This article attempts to measure employment vulnerability among women workers in Uttar Pradesh by constructing a multidimensional vulnerability index (MVI). The index is based on 23 dichotomous (binary) variables corresponding to various dimensions of vulnerability related to employment. A composite index of vulnerability is developed for each occupational category, sector of employment and gender. Here, MVI is the average of five indices which are computed for the respective dimensions of employment vulnerability. The findings suggest high levels of vulnerability among informal workers with the MVI values ranging from 0.087 (low) to 0.783 (high).The overall MVI (measured by principal component loading [PCA]) was 0.768 for the construction and domestic workers, followed by tailors (0.629) and garment workers (0.635). Appropriate policies are needed to help lift women from the cumulative neglect that they experience in unorganised labour market.

scholarly journals Frameworks and inequalities in healthcare: some applications

2021 ◽  
pp. 115-120
Author(s):  
Pietro Renzi ◽  
Alberto Franci
Keyword(s):  
Health Outcomes ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Social Inequalities ◽  
Economic Status ◽  
Determinants Of Health ◽  
Health Determinants ◽  
Quadrant Analysis ◽  
Inequality Measures ◽  
Health Objectives

Background Social determinants of health (SDOH) have increasingly entered health policy conversations as a growing body of researches, reveal the direct relationship between social determinants and health outcome. In fact, the recent literature is moving from the traditional model that focus on how health affects economic status, to a new view that economic status affects health. Objectives To investigate the principal conceptual frameworks for action on social determinants of health. Another aim is to contribute on the ongoing discourse on feasible measures which could be used to alert regions to inequalities in the distribution of health. Methodology, Italian data are used as a demonstration. Quadrant charts illustrate associations between how much regions spend on health and how effectively health system functions. The relevant inequality measures are used to rank health inequalities. Main results Frameworks have been presented to help communities, health professionals and others begin to better understand and address a variety of factors that affects health. Quadrant analysis technique shows the extent to which spending more on health, translates into better health outcomes, higher quality of care and improve access to care across the Italian regions, whilst also recognition the importance of major risk factors. Conclusions The social inequalities in health and what this means for how we understand and reduce them, as not to date been compressively examined empirically. There is an urgent need to expand our knowledge with comparable data on health determinants and more refined health outcomes. Furthermore, there is a need for feasible inequality measures in the health information systems. The measures used in this study, provide a step to inform and guide the uptake of equity-sensitive policies.

scholarly journals 4409 Indiana Clinical & Translational Science Monon Collaborative – Community Impact Hubs

2020 ◽  
Vol 4 (s1) ◽  
pp. 86-87
Author(s):  
Sarah Wiehe ◽  
David Craig ◽  
Matthew Wilcox ◽  
Emily Hardwick ◽  
Carrie Lawrence ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Focus Groups ◽  
Research Team ◽  
Health Determinants ◽  
List Type ◽  
Community Impact ◽  
Marion County ◽  
Sustainable Solutions ◽  
Environmental Scan ◽  
Key Informant

OBJECTIVES/GOALS: Conduct an environmental scan of Marion County (Indianapolis) neighborhoods using electronic medical record data, state health data, and social and economic dataDevelop strong network of community collaboratorsConduct a thorough assessment for each targeted neighborhood by listening and understanding the pressing health issues in the community and working together to design and deliver solutionsMETHODS/STUDY POPULATION: Identify measures in the 3 domains of vulnerability, health and assets for the targeted neighborhoods and conduct bivariate descriptive statistics and multivariable regression analyses to investigate association between measures of vulnerability and health outcomes.Initiate relationships with leaders and residents in targeted neighborhoodsLocate organizations working in targeted neighborhoods through online mapping software and word-of-mouth at neighborhood events, and created a spreadsheet with contact information.Conduct multidisciplinary assessment (i.e. key informant interviews, focus groups, town hall meetings) of the targeted neighborhood.Iteratively synthesize assessments to develop areas of interest and relevance to the community.Develop a road map for solutions identified by the community.RESULTS/ANTICIPATED RESULTS: The results from the environmental scan conducted will be displayed in a report and visual “map” of health outcomes and health determinants, including assets and barriers for the targeted neighborhoods. The research team will use results from the environmental scan coupled with listening activities including attendance at community events, key informant interviews and focus groups to develop relationships and strong collaborations with the targeted neighborhood stakeholders. The relationship building between the research team and community will provide increased trust and engagement that will further enhance the effectiveness of the assessments completed with the targeted neighborhood. The assessments will help to empower communities to develop sustainable solutions and drive future work that will lead to future grant applications and larger-scale implementation in other community impact hub neighborhoods. DISCUSSION/SIGNIFICANCE OF IMPACT: Through the community impact hub work, we will develop collaborative efforts with targeted neighborhoods with the greatest health inequities in the Marion County area. In partnership with these neighborhoods, we will build a foundation – a network of community collaborators and a focused plan – upon which we will improve the health outcomes of residents while learning best practices on how to do so.

scholarly journals Assessment of Livelihood Vulnerability of Fisherfolks in Coastal and Freshwater Fishing Communities of Ilaje in Ondo State

2021 ◽  
pp. 1-14
Author(s):  
Siyanbola A. Omitoyin ◽  
Adeniyi P. Ogungbure ◽  
Kemisola D. Osakuade
Keyword(s):  
Climate Change ◽  
Composite Index ◽  
Climate Change Impacts ◽  
Vulnerability Index ◽  
Coastal Communities ◽  
Fishing Communities ◽  
The Social ◽  
Ondo State ◽  
Food Vulnerability ◽  
Vulnerability Score

The study assessed the livelihood vulnerability of fisherfolks in both coastal and freshwater fishing communities of Ilaje Local Government area of Ondo state, Nigeria. Structured questionnaires were used to collect information from 200 fisherfolks from both communities. Data were analyzed using the descriptive statistics, Livelihood Vulnerability Index data were aggregated using a composite index and differential vulnerabilities were compared. The results showed that majority of the fisherfolks from freshwater and coastal communities were below 46 years old, respondents from the freshwater communities were 95% male, 5% females while all (100%) respondents in the coastal communities were male with majority assenting to fishing as their primary occupation. The freshwater communities showed greater vulnerability on the socio-demographic profile (SDP) index than coastal communities (SDP freshwater 0.49;SDPcoastal communities 0.34). Freshwater also showed greater vulnerability on the livelihood strategies component (0.45) than coastal communities (0.40). The social networks indicators were the same for the two communities. The overall health vulnerability score for freshwater communities (0.46) was higher than that for coastal communities (0.44).  Also, the overall food vulnerability score for freshwater households (0.23) was greater than that of coastal community households (0.22). Freshwater households had a lower vulnerability score (0.03) for the water component than coastal communities (0.17). Based on the incidents of flooding, droughts, storms and erosion, households in the coastal communities (0.50) were more vulnerable to natural disasters than those in the freshwater communities (0.41). Overall, coastal communities had a higher Livelihood Vulnerability Index (LVI) than freshwater (0.357 versus 0.356).This logical approach may be used to monitor vulnerability, programs and resources to assist fisherfolks. Also, there should be enlightenment on how to mitigate the factors enhancing climate change while good infrastructure and aids be given to those who suffer losses due to climate change impacts.

scholarly journals Analysing agricultural drought vulnerability at sub-district level through exposure, sensitivity and adaptive capacity based composite index

2014 ◽  
Vol XL-8 ◽  
pp. 65-70 ◽  
Author(s):  
C. S. Murthy ◽  
B. Laxman ◽  
M. V. R. Sesha Sai ◽  
P. G. Diwakar
Keyword(s):  
Adaptive Capacity ◽  
Composite Index ◽  
Vulnerability Index ◽  
The State ◽  
District Level ◽  
Agricultural Drought ◽  
Current Status ◽  
Drought Vulnerability ◽  
Related Data ◽  
Land Holdings

Information on agricultural drought vulnerability status of different regions is extremely useful for implementation of long term drought management measures. A quantitative approach for measuring agricultural drought vulnerability at sub-district level was developed and implemented in the current study, which was carried-out in Andhra Pradesh state, India with the data of main cropping season i.e., kharif. The contributing indicators represent exposure, sensitivity and adaptive capacity components of vulnerability and were drawn from weather, soil, crop, irrigation and land holdings related data. After performing data normalisation and variance based weights generation, component wise composite indices were generated. Agricultural Drought Vulnerability Index (ADVI) was generated using the three component indices and beta distribution was fitted to it. Mandals (sub-district level administrative units) of the state were categorised into 5 classes – Less vulnerable, Moderately vulnerable, Vulnerable, Highly vulnerable and Very highly vulnerable. Districts dominant with vulnerable Mandals showed considerably larger variability of detrended yields of principal crops compared to the other districts, thus validating the index based vulnerability status. Current status of agricultural drought vulnerability in the state, based on ADVI, indicated that vulnerable to very highly vulnerable group of Mandals represent 54 % of total Mandals and about 55 % of the agricultural area and 65 % of the rainfed crop area. The variability in the agricultural drought vulnerability at disaggregated level was effectively captured by ADVI. The vulnerability status map is useful for diagnostic analysis and for formulating vulnerability reduction plans.

scholarly journals An integrative study of five biological clocks in somatic and mental health

2020 ◽  
Author(s):  
Rick Jansen ◽  
Josine Verhoeven ◽  
Laura KM Han ◽  
Karolina A Aberg ◽  
Edwin CGJ van den Oord ◽  
...  
Keyword(s):  
Mental Health ◽  
Metabolic Syndrome ◽  
Mental Disorders ◽  
Composite Index ◽  
Effect Sizes ◽  
Health Determinants ◽  
Biological Clocks ◽  
Integrative Study ◽  
Male Sex ◽  
The Individual

ABSTRACTBiological clocks have been developed at different molecular levels and were found to be more advanced in the presence of somatic illnesses and mental disorders. However, it is unclear whether different biological clocks reflect similar aging processes and determinants. In ~3000 subjects, we examined whether 5 biological clocks (telomere length, epigenetic, transcriptomic, proteomic and metabolomic clocks) were interrelated and associated to somatic and mental health determinants. Correlations between biological clocks were small (all r<0.2), indicating little overlap. The most consistent associations with the advanced biological clocks were found for male sex, higher BMI, metabolic syndrome, smoking and depression. As compared to the individual clocks, a composite index of all five clocks showed most pronounced associations with health determinants. The large effect sizes of the composite index and the low correlation between biological clocks, indicate that one’s biological age is best reflected by combining aging measures from multiple cellular levels.

scholarly journals Population Health Inequalities Across and Within European Metropolitan Areas through the Lens of the EURO-HEALTHY Population Health Index

2019 ◽  
Vol 16 (5) ◽  
pp. 836 ◽  
Author(s):  
Claudia Costa ◽  
Paula Santana ◽  
Sani Dimitroulopoulou ◽  
Bo Burstrom ◽  
Carme Borrell ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Population Health ◽  
Urban Areas ◽  
Metropolitan Areas ◽  
Health Determinants ◽  
Healthy Population ◽  
Health Index ◽  
Geographical Patterns ◽  
Northern Cities ◽  
Multiple Health

The different geographical contexts seen in European metropolitan areas are reflected in the uneven distribution of health risk factors for the population. Accumulating evidence on multiple health determinants point to the importance of individual, social, economic, physical and built environment features, which can be shaped by the local authorities. The complexity of measuring health, which at the same time underscores the level of intra-urban inequalities, calls for integrated and multidimensional approaches. The aim of this study is to analyse inequalities in health determinants and health outcomes across and within nine metropolitan areas: Athens, Barcelona, Berlin-Brandenburg, Brussels, Lisbon, London, Prague, Stockholm and Turin. We use the EURO-HEALTHY Population Health Index (PHI), a tool that measures health in two components: Health Determinants and Health Outcomes. The application of this tool revealed important inequalities between metropolitan areas: Better scores were found in Northern cities when compared with their Southern and Eastern counterparts in both components. The analysis of geographical patterns within metropolitan areas showed that there are intra-urban inequalities, and, in most cities, they appear to form spatial clusters. Identifying which urban areas are measurably worse off, in either Health Determinants or Health Outcomes, or both, provides a basis for redirecting local action and for ongoing comparisons with other metropolitan areas.

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